Ping average using sliding average
Random errors in the velocity measaurements can be reduced using data from multiple pings, and then calculating the average value from these using the sliding average principle.
The acoustic Doppler current profiler (ADCP) works by transmitting constant frequency pings into the water. The velocity of the water current is calculated by measuring the time it takes for the echoes to be returned and the changes in the frequency caused by the Doppler effect.
Using only single pings for these calculations may result in velocity errors that are too large to meet the measurement requirements. For this reason, the average measurements from multiple pings are used. The average values are determined using a selected number of pings and the sliding average principle. Use the Ping Average function to specify how many pings you want to use.
The Ping Average function has effect on the quality measurements of the ADCP data. Error Velocity, Correlation filtering is performed using individual pings. Pings which matches the threshold values of these parameters or have a higher quality are used for estimating velocity. Error Velocity, Correlation filtering is performed using individual pings. Pings which matches the threshold values of these parameters or have a higher quality are used for estimating velocity. Percent Good only uses pings which have already passed Error Velocity and Correlation and makes a ping average calculation of these pings to estimate the Percent Good fraction of the velocity data.